





import requests

_snake_case    :       Tuple		       =    ''  # <-- Put your OpenWeatherMap appid here!
_snake_case    :       Dict		       =    'https://api.openweathermap.org/data/2.5/'

def     a_       (					lowerCAmelCase_ :     str = "Chicago",      lowerCAmelCase_ :     str = APPID      ):
   return requests.get(URL_BASE + 'weather',      params=locals()      ).json()

def     a_       (					lowerCAmelCase_ :     str = "Kolkata, India",      lowerCAmelCase_ :     str = APPID      ):
   return requests.get(URL_BASE + 'forecast',      params=locals()      ).json()

def     a_       (					lowerCAmelCase_ :     float = 55.68,      lowerCAmelCase_ :     float = 12.57,      lowerCAmelCase_ :     str = APPID      ):
   return requests.get(URL_BASE + 'onecall',      params=locals()      ).json()


if __name__ == "__main__":
     from pprint import pprint

     while True:
          _snake_case    :       List[str]		       =    input('Enter a location:').strip()
          if location:
               pprint(current_weather(location))
          else:
               break


"""simple docstring"""


# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a				={
    'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
    'processing_mgp_str': ['MgpstrProcessor'],
    'tokenization_mgp_str': ['MgpstrTokenizer'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=[
	    'MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'MgpstrModel',
	    'MgpstrPreTrainedModel',
	    'MgpstrForSceneTextRecognition',
	]

if TYPE_CHECKING:
	from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
	from .processing_mgp_str import MgpstrProcessor
	from .tokenization_mgp_str import MgpstrTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mgp_str import (
		    MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MgpstrForSceneTextRecognition,
		    MgpstrModel,
		    MgpstrPreTrainedModel,
		)
else:
	import sys

	a				=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


